Multi-Attribute Decision Making Methods And Applications Based On Multi-Granularity Probabilistic Linguistic Information

As an influential branch of modern decision making theory and intelligent decision making,multi-attribute decision making has been played an active role in the fields of risk decision making,applied mathematics,and emergency decision making.Due to the different complexity of real decision making problems and the fuzziness of human thinking,decisionmakers may not be able to express their evaluation information through accurate numbers but prefer linguistic information in line with human expression habits and preferences.Among all kinds of information forms,the multi-granularity probabilistic linguistic term set is not only a linguistic form conforming to people's expression habits but also giving the corresponding probability of linguistic information,which has good applicability.The multiattribute decision-making method based on it will be an important tool to solve decisionmaking problems in various fields.At this stage,the research on multi-attribute decision making based on multi-granularity probabilistic linguistic term set is just emerging.Therefore,this paper proposes several multi-granularity probabilistic linguistic multiattribute decision making methods according to different processing ideas and perspectives of multi-granularity probabilistic linguistic term sets.The specific research is divided into five parts:(1)The basic concepts of multi-granularity probabilistic linguistic term sets are proposed,including transformation function,operational laws,possibility degree and information measure.The related theories involved in this paper are briefly reviewed,such as Choquet integral and Shapley value,several classical decision making methods and disappointment theory.These concepts and theories are the theoretical basis for constructing various subsequent methods.(2)Some multi-granularity probabilistic linguistic information integration operator is constructed to deal with interaction.Including the multi-granularity probability linguistic Choquet integral operator based on ? fuzzy measure to deal with the correlation between adjacent combinations and the multi-granularity probability linguistic Shapley Choquet integral operator based on ? fuzzy measure to deal with the global correlation.Based on this operator,a multi-granularity probabilistic linguistic multi-attribute decision making method is constructed,and this method is applied to the quality evaluation of online teaching to verify its feasibility and superiority.(3)A multi-granularity probability linguistic ELECTRE-EDAS method is proposed.The combination of ELECTRE method and EDAs method avoids the complex calculation in ELECTRE method.The combination of BWM method and deviation maximization method is used to deal with the unknown attribute weight.Finally,the feasibility and superiority of the proposed method are verified by an example of sustainable medical supplier selection.(4)A multi-granularity probability linguistic MULTIMOORA method based on disappointment theory is proposed.The proposed operator,EDAS method,and disappointment theory are combined into the MULTIMOORA method,which improve the stability and rationality of the result;Based on the evaluation information given by the decision-maker,the predetermined weight of the decision-maker is further adjusted through the degree of the decision-maker's grasp of the decision-making;The combination of SWARA method and CRITIC method is used to deal with the case of unknown attribute weight.Finally,an example of distance education evaluation is given to verify the effectiveness and feasibility of the proposed method.(5)Research on service quality evaluation of platform-type cross-border e-commerce.The service quality of platform-type cross-border e-commerce is the key to customer satisfaction.To improve its competitiveness in the shopping market,the operator,attribute combination weight method and multi-attribute decision making method proposed in this paper are applied to the service quality evaluation of platform-type cross-border e-commerce to improve its competitiveness and customer satisfaction.